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140.614.95
Data Analysis Workshop II

Location
Kyoto, Japan
Term
4th Term
Department
Biostatistics
Credit(s)
2
Academic Year
2025 - 2026
Instruction Method
In-Person
Class Time(s)
Wednesday, 1:00 - 5:00pm
Thursday, 8:30am - 5:00pm
Friday, 8:30am - 5:00pm
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Prerequisite
140.613
Enrollment Restriction
Enrollment restricted to students in the Kyoto MPH cohorts
Description
Intended for students with a broad understanding of biostatistical concepts used in public health sciences who seek to develop additional data analysis skills.
Emphasizes concepts and illustration of concepts applying a variety of analytic techniques to public health datasets in a computer laboratory using Stata statistical software. Masters advanced methods of data analysis including analysis of variance, analysis of covariance, nonparametric methods for comparing groups, multiple linear regression, logistic regression, log-linear regression, and survival analysis.
Learning Objectives
Upon successfully completing this course, students will be able to:
  1. Use Stata or R to: visualize relationships between two continuous measures; fit simple linear regression models, and interpret relevant estimates from the results; fit multiple linear regression models to relate a continuous outcome to multiple predictors in one model and to help assess confounding, interaction, and goodness-of-fit; graph lowess smoothing functions to relate the probability of a dichotomous outcome to a continuous predictor; fit multiple logistic regression models to relate a dichotomous outcome to multiple predictors in one model and to help assess confounding, interaction, and goodness-of-fit; set up cohort study data survival analysis format; and fit Cox regression models to relate time-to-event data to multiple predictors in one model and to help assess confounding, interaction, and goodness-of-fit.
Upon successfully completing this course, students will be able to:
Methods of Assessment
This course is evaluated as follows:
  • 60% Lab Assignments and Quizzes
  • 40% Final Project
Special Comments

Students must have a laptop computer with Stata installed. Course meeting times are: Wednesday, March 23, 1-5; and Thursday, March 24, and Friday, March 25, 8:30-5